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蛋白质空间结构与人工智能相遇:在精准医学中彻底改变了药物协同对抗
Anqi Lin1, Chang Che2, Aimin Jiang3
1Donghai County People's Hospital (Affiliated Kangda College of Nanjing Medical University); Department of Oncology, Zhujiang Hospital, Southern Medical University, Lianyungang, 222000, China.
本综述探讨了人工智能 (AI) 和蛋白质结构如何预测药物协同作用和对抗作用,有助于针对癌症和代谢障碍等疾病的向药物开发.
科学领域:
- 计算药物发现和制药研究.
- 综合生物信息学和结构生物学.
背景情况:
- 针对性药物设计中,蛋白质位点的药物可用性至关重要.
- 了解药物协同作用和对抗作用对于有效的疗法至关重要.
- 人工智能 (AI) 为预测这些相互作用提供了新的途径.
研究的目的:
- 系统地审查人工智能驱动的方法来预测使用蛋白质3D结构的药物协同作用和对抗作用.
- 探索药物相互作用背后的分子机制.
- 评估机器学习和深度学习在药物开发中的应用.
主要方法:
- 蛋白质3D结构数据与人工智能算法的集成.
- 分子机制的分析 (转录因子,信号通路,膜传输).
- 使用多源生物数据对人工智能模型性能进行评估.
主要成果:
- 人工智能,特别是机器学习和深度学习,在预测药物协同作用-对抗作用方面取得了重大进展.
- 识别药物结合部位和优化分子对接的方法正在进步.
- 了解多向药物的机制和结构特征正在得到改善.
结论:
- 人工智能和结构生物学为精准医学和个性化治疗策略提供了坚实的基础.
- 这些进展有助于合理设计新型多向药物.
- 突出了对癌症,传染病和代谢疾病的重大临床和转化影响.
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